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Machine Learning Ai Intern Jobs in Georgia (NOW HIRING)

Cox Automotive

Machine Learning Lead Engineer

Lake City, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Marietta, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Smyrna, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Austell, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

Cox Automotive

Machine Learning Lead Engineer

Marietta, GA · On-site

$134K - $224K/yr

Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business ...

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Machine Learning Ai Intern information

What does a Machine Learning AI Intern do?

A Machine Learning AI Intern assists in developing, testing, and deploying machine learning models and algorithms under the supervision of experienced data scientists or engineers. Typical responsibilities include data preprocessing, feature engineering, model evaluation, and documentation. Interns may also help in researching new AI techniques and supporting the integration of models into existing applications. The role provides hands-on experience with machine learning tools, programming languages like Python, and frameworks such as TensorFlow or PyTorch. This internship helps build foundational skills for a career in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive as a Machine Learning AI Intern, and why are they important?

To thrive as a Machine Learning AI Intern, you need a solid foundation in mathematics, programming (often Python), and machine learning concepts, usually supported by coursework or relevant projects. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Curiosity, problem-solving ability, and strong communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills are crucial for contributing meaningfully to projects, adapting to new technologies, and growing within the fast-evolving AI field.

What types of projects do Machine Learning AI Interns typically work on during their internship?

As a Machine Learning AI Intern, you can expect to work on real-world projects such as developing predictive models, performing data preprocessing and analysis, or contributing to the improvement of existing algorithms. Interns often assist with tasks like data cleaning, feature engineering, and model evaluation, while collaborating closely with data scientists and engineers. This hands-on experience helps interns build practical skills and gain exposure to the entire machine learning workflow in a professional setting.

What is the difference between Machine Learning Ai Intern vs Data Science Intern?

AspectMachine Learning Ai InternData Science Intern
Required CredentialsRelevant coursework, programming skills, basic understanding of ML conceptsStatistics, programming, data analysis skills, often with similar educational background
Work EnvironmentTech companies, startups, research labs focusing on AI/ML projectsVariety of industries including finance, healthcare, tech, focusing on data analysis
Employer & Industry UsagePrimarily in AI/ML development teams within tech and research sectorsAcross industries for data analysis, reporting, and decision-making support

Machine Learning Ai Interns focus on developing and applying AI and ML models, often working closely with data scientists and engineers. Data Science Interns work on analyzing data, creating reports, and supporting data-driven decisions. While both roles require programming and analytical skills, ML Interns typically specialize in AI algorithms, whereas Data Science Interns focus on broader data analysis tasks.

Machine Learning Ai Intern jobs near you
Machine Learning / AI Engineer (Lead)

Machine Learning / AI Engineer (Lead)

Nexwave

Alpharetta, GA • On-site

$75/hr

Other

Posted 3 days ago

New

Job description

Job Title: Machine Learning / AI Engineer (Lead)

Location :: Alpharetta GA (OR) Oakland Bay area , CA (weekly one day in office)

Exp Req : 15-20 Yrs Max

Visa : EAD

Rate : $75/Hr on C2C/1099

Job Description

We are seeking an experienced Machine Learning / AI Engineer (Lead) to design, develop, and operationalize enterprise AI/ML solutions. The ideal candidate will have strong expertise in Azure Machine Learning, Snowflake, MLOps, Python, Generative AI, LLMs, and RAG architectures. This role will lead AI/ML best practices, build scalable production-ready models, establish governance frameworks, and collaborate with cross-functional teams to deliver innovative AI solutions.

Key Skills
  • Machine Learning & Artificial Intelligence (AI)
  • Generative AI, LLMs & RAG
  • Azure Machine Learning & Azure OpenAI
  • Snowflake, Snowpark & Snowflake Cortex
  • MLOps & Model Lifecycle Management
  • Python, Scikit-learn, TensorFlow, PyTorch, XGBoost
  • NLP & Predictive Analytics
  • Model Governance & Explainability
  • Data Engineering & Feature Engineering
  • CI/CD, Docker, Kubernetes

Regards,

Stephen

Lead Talent Acquisition Specialist

Email :

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